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Related Experiment Video

Updated: May 23, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Metab2MeSH: annotating compounds with medical subject headings.

Maureen A Sartor¹, Alex Ade, Zach Wright

¹National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA.

Bioinformatics (Oxford, England)

|April 12, 2012

Summary

Metab2MeSH automatically annotates small molecules with biomedical concepts from Medical Subject Headings. This tool links metabolites to relevant literature, addressing a gap in current bioinformatics resources.

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Area of Science:

Bioinformatics
Metabolomics
Biomedical Informatics

Background:

Genomic technologies have yielded resources linking genes to biomedical literature.
Tools for linking small molecules to physiology and literature are lacking.
Metabolomics is an emerging omics field requiring metabolite annotation.

Purpose of the Study:

To develop a tool for automatic annotation of small molecules.
To link metabolites to biomedical concepts and literature.
To complement existing databases like PubChem.

Main Methods:

Utilized a statistical approach for compound annotation.
Integrated with Medical Subject Headings (MeSH) vocabulary.
Developed the Metab2MeSH tool for automated annotation.

Main Results:

Successfully annotated small molecules with MeSH concepts.
Provided reliable and automatic annotation of compounds.
Established links from metabolites to relevant biomedical literature.

Conclusions:

Metab2MeSH addresses the need for small molecule annotation in metabolomics.
The tool enhances access to literature relevant to small molecules.
It complements existing resources by providing literature links.